Wastewater, Model Work
`Marlin derived from work by Brian Yandell
The code was derived from work by the DSI. This analysis seeks to model % of tests positive using wastewater Data. This model has logical reasons to be predictive but only finds moderate success when broken down by collection site. Particularly it consistently underpredicts the % positive rate in the P2 district.
The Original R code file can be found in the [pandemic github repository](https://github.com/UW-Madison-DataScience/pandemic/blob/master/wastewater.Rmd).
The Code for this R File can be found in the [Marlin Lee waste Water Work](https://github.com/MarlinRLee/Covid-Waste-Water-Exploration/blob/main/general%20model%20finding.Rmd)
## # A tibble: 3 x 3
## Date CovRatio PMMoVRatio
## <chr> <dbl> <dbl>
## 1 2020-12-15 1.13 2.96
## 2 2020-12-22 0.814 2.66
## 3 2021-02-18 1.30 2.21## # A tibble: 3 x 3
## Date CovRatio PMMoVRatio
## <chr> <dbl> <dbl>
## 1 2020-10-26 1.80 0.358
## 2 2020-11-16 0.326 0.0883
## 3 2021-02-08 0.645 0.0607## # A tibble: 3 x 3
## Date CovRatio PMMoVRatio
## <chr> <dbl> <dbl>
## 1 2021-02-04 7.94 0.879
## 2 2020-11-30 3.47 0.913
## 3 2021-02-11 2.08 1.15## # A tibble: 3 x 3
## Date CovRatio PMMoVRatio
## <chr> <dbl> <dbl>
## 1 2020-11-16 0.326 0.0883
## 2 2020-11-09 0.134 0.566
## 3 2021-02-01 0.126 0.970## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.06071 0.88396 1.01148 1.08913 1.20287 2.95839## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.126 0.703 0.861 1.122 1.112 7.935
Analysis with old data
## # A tibble: 189 x 14
## Site Date pH Total_Flow Conductivity TSS N1 N2
## <chr> <dttm> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Madi~ 2020-08-18 00:00:00 NA NA NA 159 12593 27108
## 2 Madi~ 2020-08-21 00:00:00 NA NA NA 120 10518. 1882.
## 3 Madi~ 2020-08-25 00:00:00 NA NA NA 199 4251 19408
## 4 Madi~ 2020-08-28 00:00:00 NA NA NA NA 17959 18937
## 5 Madi~ 2020-09-01 00:00:00 NA NA NA 207 3172 18258
## 6 Madi~ 2020-09-04 00:00:00 NA NA NA 200 7103. 13044.
## 7 Madi~ 2020-09-08 00:00:00 NA NA NA 190 NA 14897.
## 8 Madi~ 2020-09-11 00:00:00 NA NA NA 222 115224. 54012.
## 9 Madi~ 2020-09-15 00:00:00 7.77 44.8 NA 207 63618. 32447.
## 10 Madi~ 2020-09-19 00:00:00 7.65 46.7 NA 254 11442. 9003.
## # ... with 179 more rows, and 6 more variables: AVG <dbl>, PMMoV <dbl>,
## # Pct_BCoV <dbl>, Comment <chr>, `TSS (mg/L)` <dbl>, wt <dbl>## # A tibble: 3 x 2
## Date CovRatio
## <date> <dbl>
## 1 2020-10-26 1.73
## 2 2020-10-06 1.70
## 3 2020-11-23 1.58## # A tibble: 3 x 2
## Date CovRatio
## <date> <dbl>
## 1 2020-11-16 0.432
## 2 2020-09-29 0.219
## 3 2020-11-09 0.135## # A tibble: 3 x 2
## Date CovRatioN1
## <date> <dbl>
## 1 2020-10-26 1.73
## 2 2020-10-06 1.59
## 3 2020-11-23 1.30## # A tibble: 3 x 2
## Date CovRatioN1
## <date> <dbl>
## 1 2020-09-29 0.399
## 2 2020-11-16 0.326
## 3 2020-11-09 0.131## # A tibble: 3 x 2
## Date CovRatioN2
## <date> <dbl>
## 1 2020-10-06 1.73
## 2 2020-11-23 1.67
## 3 2020-11-17 0.723## # A tibble: 3 x 2
## Date CovRatioN2
## <date> <dbl>
## 1 2020-09-28 0.549
## 2 2020-11-24 0.530
## 3 2020-09-29 0.120## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.1353 0.5588 0.7004 0.8040 0.8177 1.7299## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.1312 0.4889 0.8434 0.8451 1.0915 1.7299## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 0.1203 0.5490 0.6134 0.7980 0.7233 1.7308 9
